Name
Abstract | ||
|---|---|---|
An incessant rhythm of data breaches, data leaks, and privacy exposure highlights the need to improve control over potentially sensitive data. History has shown that neither public nor private sector organizations are immune. Lax data handling, incidental leakage, and adversarial breaches are all contributing factors. Prudent organizations should consider the sensitive nature of network security data. Logged events often contain data elements that are directly correlated with sensitive information about people and their activities - often at the same level of detail as sensor data. Our intent is to produce a database which holds network security data representative of people's interaction with the network mid-points and end-points without the problems of identifiability. In this paper we discuss architectures and propose a system design that supports a risk based approach to privacy preserving data publication of network security data that enables network security data analytics research. |
Year | Venue | Field |
|---|---|---|
2018 | PROCEEDINGS OF THE 51ST ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS) | Data science,Data analysis,Computer science,Network security,Knowledge management,Systems design |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark E. DeYoung | 1 | 0 | 0.34 |
| Philip Kobezak | 2 | 0 | 0.68 |
| David R. Raymond | 3 | 177 | 7.97 |
| randy marchany | 4 | 175 | 15.88 |
| joseph g tront | 5 | 149 | 24.97 |